Design patterns: elements of reusable object-oriented software
Design patterns: elements of reusable object-oriented software
Modular visualization environments: past, present, and future
ACM SIGGRAPH Computer Graphics - Special focus: modular visualization environments (MVEs)
An extended data-flow architecture for data analysis and visualization
ACM SIGGRAPH Computer Graphics - Special focus: modular visualization environments (MVEs)
Pattern-oriented software architecture: a system of patterns
Pattern-oriented software architecture: a system of patterns
The visualization toolkit (2nd ed.): an object-oriented approach to 3D graphics
The visualization toolkit (2nd ed.): an object-oriented approach to 3D graphics
The Application Visualization System: A Computational Environment for Scientific Visualization
IEEE Computer Graphics and Applications
Large-Scale Data Visualization Using Parallel Data Streaming
IEEE Computer Graphics and Applications
Visualizing Time-Varying Volume Data
Computing in Science and Engineering
EGVE '03 Proceedings of the workshop on Virtual environments 2003
A Taxonomy of Visualization Techniques Using the Data State Reference Model
INFOVIS '00 Proceedings of the IEEE Symposium on Information Vizualization 2000
An architecture for a scientific visualization system
VIS '92 Proceedings of the 3rd conference on Visualization '92
Interactive Terascale Particle Visualization
VIS '04 Proceedings of the conference on Visualization '04
Proceedings of the 2004 ACM/IEEE conference on Supercomputing
Topological Methods for 2D Time-Dependent Vector Fields Based on Stream Lines and Path Lines
IEEE Transactions on Visualization and Computer Graphics
Corrections to "Time Dependent Processing in a Parallel Pipeline Architecture'
IEEE Transactions on Visualization and Computer Graphics
Parallel volume rendering on the IBM Blue Gene/P
EG PGV'08 Proceedings of the 8th Eurographics conference on Parallel Graphics and Visualization
Volumetric evaluation of meshless data from smoothed particle hydrodynamics simulations
VG'10 Proceedings of the 8th IEEE/EG international conference on Volume Graphics
Streaming-enabled parallel dataflow architecture for multicore systems
EuroVis'10 Proceedings of the 12th Eurographics / IEEE - VGTC conference on Visualization
A classification of scientific visualization algorithms for massive threading
UltraVis '13 Proceedings of the 8th International Workshop on Ultrascale Visualization
A model for optimizing file access patterns using spatio-temporal parallelism
UltraVis '13 Proceedings of the 8th International Workshop on Ultrascale Visualization
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Pipeline architectures provide a versatile and efficient mechanism for constructing visualizations, and they have been implemented in numerous libraries and applications over the past two decades. In addition to allowing developers and users to freely combine algorithms, visualization pipelines have proven to work well when streaming data and scale well on parallel distributed-memory computers.However, current pipeline visualization frameworks have a critical flaw: they are unable to manage time varying data.As data flows through the pipeline, each algorithm has access to only a single snapshot in time of the data. This prevents the implementation of algorithms that do any temporal processing such as particle tracing; plotting over time; or interpolation, fitting, or smoothing of time series data. As data acquisition technology improves, as simulation time-integration techniques become more complex, and as simulations save less frequently and regularly, the ability to analyze the time-behavior of data becomes more important. This paper describes a modification to the traditional pipeline architecture that allows it to accommodate temporal algorithms. Furthermore, the architecture allows temporal algorithms to be used in conjunction with algorithms expecting a single time snapshot, thus simplifying software design and allowing adoption into existing pipeline frameworks.Our architecture also continues to work well in parallel distributed-memory environments.We demonstrate our architecture by modifying the popular VTK framework and exposing the functionality to the ParaView application.We use this framework to apply time-dependent algorithms on large data with a parallel cluster computer and thereby exercise a functionality that previously did not exist.